Reading Chicago Reading: Modeling Texts and Readers in a Public Library System

A pilot study on how analyzing patron responses to a citywide reading program can help scholars and librarians better understand which book genres and styles prove most meaningful to the community.

“Reading Chicago Reading” aims to put new data-intensive predictive tools in the hands of public librarians and digital humanities scholars in order to enhance their ability to serve public needs and interests. We take as our starting point the Chicago Public Library’s popular and muchimitated “One Book One Chicago” program, in which books are annually selected for city-wide promotion. Our project combines circulation data, social media postings, text analysis, branch-bybranch demographics, and history of the events of themselves to recover quantitative, predictive factors that link texts to reader response. The multi-disciplinary project brings together expertise in library science, text mining, predictive modeling and machine learning, literature, and urban sociology, and builds on existing collaborations with the Chicago Public Library.